缩放
三角积分调变
计算机科学
带宽(计算)
物理
计算机网络
光学
镜头(地质)
作者
Zongnan Wang,Lu Jie,Zichen Kong,Mingtao Zhan,Yi Zhong,Yuan Wang,Xiyuan Tang
标识
DOI:10.1109/isscc42615.2023.10067696
摘要
Many $\text{IoT}$ applications demand ADCs with high resolution, medium bandwidth, and good energy efficiency. Lately, the incremental ADC is drawing r ising attention by favoring system integration with its easy multiplexing and simple digital filtering. By combining a low-power SAR with a low-distortion $\Delta\Sigma$ modulator, the zoom architecture achieves high energy efficiency and high resolution simultaneously [1–2]. However, the conventional zoom ADC can only convert quasi-static signals, since the two stages operate sequentially, and its $\Delta\Sigma$ conversion operates at a slow speed. The dynami c zoom architecture performs coarse and fine conversions concurrently, thus being able to convert varying inputs [3–4]. Yet, limited by the low quantization level of the fine $\Delta\Sigma \mathrm{M}$ , it requires a large OSR for the targeted resolution (e.g., 282.25 in [3] and 87.5 in [4]), which restricts the input bandwidth to several tens of $\text{kHz}$ , Moreover, its loop filter relies on charge transfer, where each conversion requires dedicated sampling for its residue generation. As a result, in addition to the limited input bandwidth, the largely repeated sampling operation incurs extra power and design challenge for input drivers. The CT zoom architecture features easy driving while still requiring a large conversion cycle of 8192 in [5]. Recently, the emerging noise-shaping (NS) SAR ADC employs the efficient SAR for the multi-bit quantizer, significantly reducing conversion cycles [6–7]. However, without the initial coarse quantization, high loop filter orders are usually required for hig h -resolution applications, raising significant hardware cost and design complexity.
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